Prior COVID and vaccination generate superior hybrid immunity Immunity Coronavirus Disease COVID SARSCoV2 ScienceTM
To this end, they compared SARS-CoV-2 spike -specific immunity among unvaccinated and vaccinated SARS-CoV-2 convalescent individuals and coronavirus disease 2019 -naïve vaccinated individuals.
Researchers need these insights because despite large-scale COVID-19 vaccine coverage, people, especially in Western countries, are still experiencing SARS-CoV-2 reinfection. However, the belief that hybrid immunity confers superior protection against the virus requires experimental validation. About the study In the present study, researchers performed a longitudinal analysis on 613 individuals and broadly categorized the groups as follows:
In addition, they monitored the occurrence of breakthrough infections in all study groups using the bioMerieux Vidas assay that measured RBD IgG titers against the SARS-CoV-2 nucleocapsid antigen. The rebound of RBD-specific nAb titers indicated breakthrough infection, not their steady decline. Kotaki et al. proved this in humans in the context of SARS-CoV-2 vaccinated people. They showed that the mBCs pool preserved broadly reactive Abs specificities that recognized the Delta and Omicron SARS-CoV-2 variants but not their sera.
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Post COVID-19 irritable bowel syndromeObjectives The long-term consequences of COVID-19 infection on the gastrointestinal tract remain unclear. Here, we aimed to evaluate the prevalence of gastrointestinal symptoms and post-COVID-19 disorders of gut–brain interaction after hospitalisation for SARS-CoV-2 infection. Design GI-COVID-19 is a prospective, multicentre, controlled study. Patients with and without COVID-19 diagnosis were evaluated on hospital admission and after 1, 6 and 12 months post hospitalisation. Gastrointestinal symptoms, anxiety and depression were assessed using validated questionnaires. Results The study included 2183 hospitalised patients. The primary analysis included a total of 883 patients (614 patients with COVID-19 and 269 controls) due to the exclusion of patients with pre-existing gastrointestinal symptoms and/or surgery. At enrolment, gastrointestinal symptoms were more frequent among patients with COVID-19 than in the control group (59.3% vs 39.7%, p|0.001). At the 12-month follow-up, constipation and hard stools were significantly more prevalent in controls than in patients with COVID-19 (16% vs 9.6%, p=0.019 and 17.7% vs 10.9%, p=0.011, respectively). Compared with controls, patients with COVID-19 reported higher rates of irritable bowel syndrome (IBS) according to Rome IV criteria: 0.5% versus 3.2%, p=0.045. Factors significantly associated with IBS diagnosis included history of allergies, chronic intake of proton pump inhibitors and presence of dyspnoea. At the 6-month follow-up, the rate of patients with COVID-19 fulfilling the criteria for depression was higher than among controls. Conclusion Compared with controls, hospitalised patients with COVID-19 had fewer problems of constipation and hard stools at 12 months after acute infection. Patients with COVID-19 had significantly higher rates of IBS than controls. Trial registration number [NCT04691895][1]. Data are available upon reasonable request. Data are available on reasonable request. All figures have associated ra
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Saudi leads push to elevate carbon removal in UN climate science report\n\t\t\tExpert insights, analysis and smart data help you cut through the noise to spot trends,\n\t\t\trisks and opportunities.\n\t\t\n\t\tJoin over 300,000 Finance professionals who already subscribe to the FT.
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Saudi leads push to elevate carbon removal in UN climate science report\n\t\t\tExpert insights, analysis and smart data help you cut through the noise to spot trends,\n\t\t\trisks and opportunities.\n\t\t\n\t\tJoin over 300,000 Finance professionals who already subscribe to the FT.
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An artificial intelligence approach for predicting death or organ failure after hospitalization for COVID-19: development of a novel risk prediction tool and comparisons with ISARIC-4C, CURB-65, qSOFA, and MEWS scoring systems - Respiratory ResearchBackground We applied machine learning (ML) algorithms to generate a risk prediction tool [Collaboration for Risk Evaluation in COVID-19 (CORE-COVID-19)] for predicting the composite of 30-day endotracheal intubation, intravenous administration of vasopressors, or death after COVID-19 hospitalization and compared it with the existing risk scores. Methods This is a retrospective study of adults hospitalized with COVID-19 from March 2020 to February 2021. Patients, each with 92 variables, and one composite outcome underwent feature selection process to identify the most predictive variables. Selected variables were modeled to build four ML algorithms (artificial neural network, support vector machine, gradient boosting machine, and Logistic regression) and an ensemble model to generate a CORE-COVID-19 model to predict the composite outcome and compared with existing risk prediction scores. The net benefit for clinical use of each model was assessed by decision curve analysis. Results Of 1796 patients, 278 (15%) patients reached primary outcome. Six most predictive features were identified. Four ML algorithms achieved comparable discrimination (P | 0.827) with c-statistics ranged 0.849–0.856, calibration slopes 0.911–1.173, and Hosmer–Lemeshow P | 0.141 in validation dataset. These 6-variable fitted CORE-COVID-19 model revealed a c-statistic of 0.880, which was significantly (P | 0.04) higher than ISARIC-4C (0.751), CURB-65 (0.735), qSOFA (0.676), and MEWS (0.674) for outcome prediction. The net benefit of the CORE-COVID-19 model was greater than that of the existing risk scores. Conclusion The CORE-COVID-19 model accurately assigned 88% of patients who potentially progressed to 30-day composite events and revealed improved performance over existing risk scores, indicating its potential utility in clinical practice.
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VAI-B: a multicenter platform for the external validation of artificial intelligence algorithms in breast imagingThe Journal of Medical Imaging (JMI) allows for the peer-reviewed communication and archiving of fundamental and translational research, as well as applications, focused on medical imaging, a field that continues to benefit from technological improvements and yield biomedical advancements in the early detection, diagnostics, and therapy of disease as well as in the understanding of normal conditions.
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